Projects in Digital Humanities Master Program

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Related lectures (32)

Logistic Regression: Fundamentals and Applications Log in to Mediaspace to watch this video

Explores logistic regression fundamentals, including cost functions, regularization, and classification boundaries, with practical examples using scikit-learn.

Machine Learning Fundamentals: Structure Discovery, Classification, Regression Log in to Mediaspace to watch this video

Covers fundamental machine learning concepts including Structure Discovery, Classification, and Regression.

Linear Models for Classification: Logistic Regression and SVM Log in to Mediaspace to watch this video

Covers linear models for classification, focusing on logistic regression and support vector machines.

Machine Learning for Physicists/Chemists: Image Classification Log in to Mediaspace to watch this video

Covers the fundamentals of machine learning for physicists and chemists, focusing on image classification tasks using artificial intelligence.

Gaussian Naive Bayes & K-NN Log in to Mediaspace to watch this video

Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

Binary Classification by Regression: Decision Functions and Cost Functions Log in to Mediaspace to watch this video

Explores binary classification by regression, decision functions, and various cost functions.

Support Vector Machines: Interactive Class Log in to Mediaspace to watch this video

Explores Support Vector Machines in machine learning, discussing SVM, support vectors, uniqueness of solutions, and multi-class SVM.

Image Classification: Decision Trees & Random Forests Log in to Mediaspace to watch this video

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Machine Learning: Supervised and Unsupervised Learning Techniques Log in to Mediaspace to watch this video

Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.

Machine Learning Applications: Regression and Classification Log in to Mediaspace to watch this video

Explores machine learning applications in materials modeling, covering regression, classification, and feature selection.

Classification Algorithms: Generative and Discriminative Approaches Log in to Mediaspace to watch this video

Explores generative and discriminative classification algorithms, emphasizing their applications and differences in machine learning tasks.

Kernel Methods: Understanding Overfitting and Model Selection Log in to Mediaspace to watch this video

Discusses kernel methods, focusing on overfitting, model selection, and kernel functions in machine learning.

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